Introduction

This document describes the re-estimation of the VE Multimodal Module (VE-MM) using the 2017 National Household Travel Survey (2017 NHTS). The original version of the VE-MM was estimated using the 2009 NHTS.

The models described in this memo include:

  • regression models used to predict household average annual daily vehicle miles traveled (AADVMT)
  • models used to predict transit, bicycle, and walking trips and person miles traveled (note that these are not included in this draft)

AADVMT Model

Estimation Data

Data Sources

Data used to estimate the VE-MM models came from several sources. The 2017 NHTS confidential data were obtained from ORNL via FHWA. The data were provided with Census Block Group which allowed data from the EPA Smart Location Database, version 3 (SLD) to be connected to the household. Additional spatial information at the metropolitan area level were added to the data including transit revenue miles from the National Transit Database and freeway lane miles from FHWA published data.

AADVMT and DVMT Data

The AADVMT model is estimated using the total annual miles driven by vehicles owned by the NHTS households divided by 365, instead of estimating a daily VMT model based on the reported travel during the survey day. The distributions of those travel amounts differs in the data.

In particular there are a lot of “zero days” in the survey data for the survey day. There are also more very long days in the survey data with more than 200 miles of travel reported. With the averaging over the year that takes place by using AADVMT, a lot of the day to day variability within a household’s travel is removed. The final chart compares the none-zero day distribution and other than the extremes at the low end and high end of the distribution, the distributions are reasonably comparable.

One adjustment has been made to the AADVMT data, and that is to add to it shared vehicle DVMT from the travel reported ont he survey day. This is because a later model in the VisionEval system takes a portion of the estimated Dvmt from the household and allocated it to car services, so estimating the AADVMT without shared vehicle DVMT would be inconsistent with how the model is applied. The proportion of household DVMT that is shared vehicle DVMT is small for households that own private vehicles, but accounts for all non-transit vehicle based DVMT for households that do not own vehicles.

Distribution of AADVMT per Household in the 2017 NHTS

Figure 1: Distribution of AADVMT per Household in the 2017 NHTS

Distribution of Survey Day DVMT per Household in the 2017 NHTS

Figure 2: Distribution of Survey Day DVMT per Household in the 2017 NHTS

Comparison between AADVMT and Survey Day DVMT per Household in the 2017 NHTS

Figure 3: Comparison between AADVMT and Survey Day DVMT per Household in the 2017 NHTS

Comparison between AADVMT and Shared Vehicle DVMT per Household in the 2017 NHTS

Figure 4: Comparison between AADVMT and Shared Vehicle DVMT per Household in the 2017 NHTS

AADVMT Outlier Filtering

The households with the highest 1% of AADVMT were excluded from the estimation dataset. The exclusion of outliers has the effect of reducing the average AADVMT per household. The table below shows the impact on the average AADVMT per household for metro and non-metro households. The charts shows the change in the binned distribution of households for metro and non-metro households.

All of the analysis in the remainder of this document is based on the 2017 NHTS data with outliers removed, consistent with the set of households used for estimation.

Outlier Status Metro HH Non-Metro HH Metro Avg. AADVMT Non-Metro Avg. AADVMT
Included 71657 56729 51.89 66.55
Outlier 700 610 449.42 435.45
Total 72357 57339 56.10 71.34
Impacts of Outlier Filtering on the AADVMT per Household in the 2017 NHTS

Figure 5: Impacts of Outlier Filtering on the AADVMT per Household in the 2017 NHTS

Population Density (D1B)

One of the important explanatory variables for household AADVMT is the population density of the neighborhood in which the household resides. The 2017 NHTS data were linked to the SLD and the D1B variable, which contains the Census Block Group population density in units of persons per acre. The ranges of density varies significantly in the sample of NHTS households. As is expected, most non-metro households live in low density areas while the range of densities for metropolitan households is generally higher but covers several orders of magnitude. The following box plot, plotted on a log scale shows the distribution of households by population density.

Distribution of Households in the 2017 NHTS by Population Density

Figure 6: Distribution of Households in the 2017 NHTS by Population Density

The following charts show the relationship between AADVMT in low, medium, and high density areas, split by metro and non-metro households in low and medium density areas, and showing just metropolitan households in the high density chart. The trends in the charts show a clear relationship between density and AADVMT: as density increases, AADVMT tends to fall. There are some anomalous values, particular for non-metropolitan households, due to small sample sizes.

2017 NHTS AADVMT by Density for Households in Low Density Neighborhoods

Figure 7: 2017 NHTS AADVMT by Density for Households in Low Density Neighborhoods

2017 NHTS AADVMT by Density for Households in Medium Density Neighborhoods

Figure 8: 2017 NHTS AADVMT by Density for Households in Medium Density Neighborhoods

2017 NHTS AADVMT by Density for Households in High Density Neighborhoods

Figure 9: 2017 NHTS AADVMT by Density for Households in High Density Neighborhoods

Household Income

Household income has a positive impact on the amount of travel a household makes, with higher income households traveling more. The first chart shows the distribution of income levels amongst the households in the 2017 NHTS sample.

Just over 4,000 (3%) of the households in the sample were missing a response to the household income question. For the purpose of this analysis they have been recoded with an income in the median income category, which has a midpoint of $62,500.

The second chart shows the relationship between AADVMT and household income and shows shows a clear postiive trend for both metropolitan and non-metropolitan households.

Distribution of Households in the 2017 NHTS by Household Income

Figure 10: Distribution of Households in the 2017 NHTS by Household Income

2017 NHTS AADVMT by Household Income

Figure 11: 2017 NHTS AADVMT by Household Income

Household Size

Household size has a positive impact on the amount of travel a household makes, with larger households traveling more. The first chart shows the distribution of household size amongst the households in the 2017 NHTS sample. The second charts shows the relationship between AADVMT and household size and shows shows a clear postiive trend for both metropolitan and non-metropolitan households.

Distribution of Households in the 2017 NHTS by Household Size

Figure 12: Distribution of Households in the 2017 NHTS by Household Size

2017 NHTS AADVMT by Household Size

Figure 13: 2017 NHTS AADVMT by Household Size

Household life cycle stage

The household’s life cycle stage, i.e., whether the household is a single person, a couple without children, a couple with children, or older “empty nesters” influences the amount of travel a household makes. Multi person household make more travel and adding children to the household causes a further moderate increase in the amount of travel. The first chart shows the distribution of life cycle stage amongst the households in the 2017 NHTS sample. The second charts shows the relationship between AADVMT and household life cycle stage for both metropolitan and non-metropolitan households.

Distribution of Households in the 2017 NHTS by Household Life Cycle Stage

Figure 14: Distribution of Households in the 2017 NHTS by Household Life Cycle Stage

2017 NHTS AADVMT by Household Life Cycle Stage

Figure 15: 2017 NHTS AADVMT by Household Life Cycle Stage

Number of Workers

The number of workers in the household positively impacts the amount of travel a household makes. With each additional worker in the household, the household make more travel. The first chart shows the distribution of number of workers per households amongst the households in the 2017 NHTS sample. The second charts shows the relationship between AADVMT and number of workers per household for both metropolitan and non-metropolitan households.

Distribution of Households in the 2017 NHTS by Number of Workers in the Household

Figure 16: Distribution of Households in the 2017 NHTS by Number of Workers in the Household

2017 NHTS AADVMT by Number of Workers in the Household

Figure 17: 2017 NHTS AADVMT by Number of Workers in the Household

Number of Drivers

The number of drivers in the household positively impacts the amount of travel a household makes. With each additional driver in the household, the household make more travel. The first chart shows the distribution of number of drivers per households amongst the households in the 2017 NHTS sample. The second charts shows the relationship between AADVMT and number of drivers per household for both metropolitan and non-metropolitan households.

Distribution of Households in the 2017 NHTS by Number of Drivers in the Household

Figure 18: Distribution of Households in the 2017 NHTS by Number of Drivers in the Household

2017 NHTS AADVMT by Number of Drivers in the Household

Figure 19: 2017 NHTS AADVMT by Number of Drivers in the Household

Oregon Households

The 2017 NHTS sample includes some households in Oregon. Oregon was not an “add on” state and therefore has sample from just the all-US sample, a total of 385 households. Average AADVMt per household in metro areas is slightly lower in Oregon than the average for the rest of the US, and is significantly lower for non-metro households.

State Metro HH Non-Metro HH Metro Avg. AADVMT Non-Metro Avg. AADVMT
Oregon 235 148 54.38 59.94
Other State 71422 56581 51.85 66.65

The income distribution for the Oregon households is reasonably similar to that for the other states, with a notable difference being a low number of high income households in non-metro areas. The positive effect of income of AADVMT is clear, although it is negligible across the upper categories in metro areas. The data for non-metro areas is less reliable for the high income categories due to small sample sizes.

Oregon and Other State Household Income Distribution

Figure 20: Oregon and Other State Household Income Distribution

Oregon and Other State AADVMT by Household Income

Figure 21: Oregon and Other State AADVMT by Household Income

Model Estimation

2017 NHTS AADVMT Model

The following table shows the AADVMT model estimated using the 2017 NHTS for Metro areas and Non-Metro area.

Regression model summary for 2017 AADVMT Model for Metro Areas and Non-Metro Areas
Dependent variable:
AADVMT
NONMETRO METRO
(1) (2)
Drivers 0.804*** (0.013) 0.921*** (0.010)
HhSize 0.143*** (0.012)
Workers 0.307*** (0.011) 0.198*** (0.010)
CENSUS_RNE -0.077*** (0.021) -0.113*** (0.018)
CENSUS_RS 0.114*** (0.015) 0.044*** (0.016)
CENSUS_RW -0.187*** (0.019) -0.087*** (0.017)
FwyLaneMiPC 96.537*** (19.384)
LogIncomeK 0.324*** (0.008) 0.196*** (0.007)
Age0to14 0.007 (0.014) 0.076*** (0.011)
Age65Plus -0.064*** (0.012) -0.100*** (0.011)
log1p(VehPerDriver) 3.324*** (0.028) 3.635*** (0.024)
LifeCycleCouple w/o children -0.039 (0.024) -0.122*** (0.018)
LifeCycleEmpty Nester -0.262*** (0.029) -0.529*** (0.023)
LifeCycleSingle -0.269*** (0.032) -0.504*** (0.021)
D1B -0.019*** (0.003) -0.002*** (0.0002)
D2A_EPHHM -0.166*** (0.033)
D1B:D2A_EPHHM 0.018*** (0.006)
D2A_WRKEMP 0.0003 (0.0002)
D3bpo4 -0.001*** (0.0002)
TranRevMiPC:D4c -0.062*** (0.005)
Constant 0.052 (0.050) 0.343*** (0.035)
Observations 56,634 71,657
R2 0.557 0.611
Adjusted R2 0.557 0.611
Residual Std. Error 1.337 (df = 56617) 1.576 (df = 71639)
F Statistic 4,449.198*** (df = 16; 56617) 6,608.985*** (df = 17; 71639)
Note: p<0.1; p<0.05; p<0.01

The following tables compare the AADVMT models estimated using the 2009 and 2017 NHTS.

This first comparison is between 2009 and 2017 AADVMT Models for Metro areas.

VarName NHTS2009 NHTS2017 Ratio
(Intercept) -1.333 0.343 -0.257
Age0to14 0.107 0.076 0.717
Age65Plus -0.075 -0.100 1.345
CENSUS_RNE -0.109 -0.113 1.038
CENSUS_RS 0.051 0.044 0.865
CENSUS_RW -0.092 -0.087 0.942
D1B -0.003 -0.002 0.712
D2A_WRKEMP 0.000 0.000 -1.153
D3bpo4 -0.001 -0.001 0.857
Drivers 0.705 0.921 1.307
FwyLaneMiPC 101.341 96.537 0.953
LifeCycleCouple w/o children -0.036 -0.122 3.365
LifeCycleEmpty Nester -0.256 -0.529 2.064
LifeCycleSingle -0.234 -0.504 2.157
LogIncome 0.268 0.000 0.000
LogIncomeK 0.000 0.196 Inf
TranRevMiPC:D4c -0.020 -0.062 3.130
Workers 0.186 0.198 1.065
log1p(VehPerDriver) 1.794 3.635 2.027

This second comparison is between 2009 and 2017 AADVMT Models for Non-Metro areas.

VarName NHTS2009 NHTS2017 Ratio
(Intercept) -1.416 0.052 -0.037
Age0to14 0.102 0.007 0.071
Age65Plus -0.077 -0.064 0.832
CENSUS_RNE -0.112 -0.077 0.690
CENSUS_RS 0.058 0.114 1.954
CENSUS_RW -0.176 -0.187 1.062
D1B -0.008 -0.019 2.389
D1B:D2A_EPHHM -0.027 0.018 -0.659
D2A_EPHHM -0.084 -0.166 1.971
Drivers 0.744 0.804 1.081
HhSize 0.017 0.143 8.502
LifeCycleCouple w/o children -0.013 -0.039 2.859
LifeCycleEmpty Nester -0.208 -0.262 1.259
LifeCycleSingle -0.216 -0.269 1.246
LogIncome 0.288 0.000 0.000
LogIncomeK 0.000 0.324 Inf
Workers 0.177 0.307 1.736
log1p(VehPerDriver) 1.852 3.324 1.795

2017 NHTS AADVMT Model Adjustment

One aspect of the NHTS AADVMT data that is hard to capture, even with a power transform adjusted linear model, is the variability in the data due to unobserved household travel characteristics. Some households just travel more or less than other similar households with similar income, transportation access, and neighborhood characteristics.

In order to capture this dispersion, a random variable factor has been drawn for each household to factor the predicted AADVMT to simulate household to household variation. This random variable is drawn from a left skewed normal distribution to allow for some households to have lower AADVMT, to overall achieve a slight increase in AADVMT to account for systematic under prediction of the mean AADVMT in the sample, and to produce a longer tail of households with a higher AADVMT.

Skewed Normal Distribution

Figure 22: Skewed Normal Distribution

Model Prediction Testing

Households by Metro and Non-Metro

Metro or Non-Metro Weighted HH NHTS2017 AADVMT/HH Model AADVMT/HH Model Sim AADVMT/HH Ratio Model/NHTS2017 Ratio Model Sim/NHTS2017
metro 81845.23 51.89 46.30 51.26 0.89 0.99
non_metro 46310.07 66.59 60.81 65.92 0.91 0.99
Scatterplot of Model Prediction vs. 2017 NHTS Data

Figure 23: Scatterplot of Model Prediction vs. 2017 NHTS Data

Scatterplot of Model Prediction (Simulated) vs. 2017 NHTS Data

(#fig:scatter-aadvmt-model-prediction_rnd)Scatterplot of Model Prediction (Simulated) vs. 2017 NHTS Data

Households by DVMT Bins, Model Prediction vs. 2017 NHTS Data

Figure 24: Households by DVMT Bins, Model Prediction vs. 2017 NHTS Data

Difference in Households in DVMT Bins (Model Prediction - 2017 NHTS Data)

Figure 25: Difference in Households in DVMT Bins (Model Prediction - 2017 NHTS Data)

Difference in Households in DVMT Bins (Model Prediction (Simulated) - 2017 NHTS Data)

Figure 26: Difference in Households in DVMT Bins (Model Prediction (Simulated) - 2017 NHTS Data)

Difference in Households in DVMT Bins (Model Prediction and Simulated - 2017 NHTS Data)

Figure 27: Difference in Households in DVMT Bins (Model Prediction and Simulated - 2017 NHTS Data)

Households by Income

HH Income Metro WgtHH Non-Metro WgtHH Metro Obs AADVMT/HH Non-Metro Obs AADVMT/HH Metro Pred AADVMT/HH Non-Metro Pred AADVMT/HH Metro Sim AADVMT/HH Non-Metro Sim AADVMT/HH Metro Ratio Pred/Obs Non-Metro Ratio Pred/Obs Metro Ratio Sim/Obs Non-Metro Ratio Sim/Obs
5000 6098.98 3268.53 22.46 27.14 16.80 20.06 18.68 21.29 0.75 0.74 0.83 0.78
12500 4378.13 3135.27 25.07 33.78 21.57 29.62 23.88 32.63 0.86 0.88 0.95 0.97
19999 7376.26 4789.67 33.86 44.85 29.51 39.16 32.86 42.08 0.87 0.87 0.97 0.94
30000 7572.73 4878.84 41.43 51.67 36.34 46.80 40.26 50.64 0.88 0.91 0.97 0.98
42499 9547.81 5845.41 48.67 63.41 42.11 57.40 46.72 62.63 0.87 0.91 0.96 0.99
62500 15183.09 9343.69 52.28 71.06 46.65 65.93 51.80 71.08 0.89 0.93 0.99 1.00
87500 9832.79 5437.34 61.49 84.90 54.69 78.94 60.76 85.26 0.89 0.93 0.99 1.00
112500 7614.83 4017.86 68.71 93.78 63.02 84.26 69.65 91.19 0.92 0.90 1.01 0.97
137500 4496.84 2112.80 74.11 96.00 65.98 90.84 72.72 100.12 0.89 0.95 0.98 1.04
174999 4680.01 1771.34 72.82 98.88 68.78 92.22 75.56 99.79 0.94 0.93 1.04 1.01
249999 5063.77 1709.32 74.27 100.15 69.69 97.92 76.78 107.47 0.94 0.98 1.03 1.07
Households by Income Group, Model Prediction vs. 2017 NHTS Data

Figure 28: Households by Income Group, Model Prediction vs. 2017 NHTS Data

Scatterplot of Model Prediction vs. 2017 NHTS Data by Income

Figure 29: Scatterplot of Model Prediction vs. 2017 NHTS Data by Income

Households by Density

D1B Group Metro WgtHH Non-Metro WgtHH Metro Obs AADVMT/HH Non-Metro Obs AADVMT/HH Metro Pred AADVMT/HH Non-Metro Pred AADVMT/HH Metro Sim AADVMT/HH Non-Metro Sim AADVMT/HH Metro Ratio Pred/Obs Non-Metro Ratio Pred/Obs Metro Ratio Sim/Obs Non-Metro Ratio Sim/Obs
0 50654.26 45046.56 57.62 67.01 51.79 61.17 57.33 66.32 0.90 0.91 0.99 0.99
10 17484.46 1100.20 49.15 52.61 44.13 48.81 48.85 52.42 0.90 0.93 0.99 1.00
20 4808.52 106.23 44.86 54.22 38.31 42.73 42.41 45.82 0.85 0.79 0.95 0.85
30 2442.89 33.11 39.41 37.81 31.30 56.72 34.40 61.88 0.79 1.50 0.87 1.64
40 1373.45 23.97 34.47 13.95 30.10 28.82 33.53 29.51 0.87 2.07 0.97 2.12
50 980.85 0.00 26.32 0.00 24.73 0.00 27.33 0.00 0.94 0.00 1.04 0.00
60 648.27 0.00 27.53 0.00 25.01 0.00 29.78 0.00 0.91 0.00 1.08 0.00
70 445.27 0.00 21.43 0.00 20.03 0.00 22.70 0.00 0.93 0.00 1.06 0.00
80 386.24 0.00 27.54 0.00 20.81 0.00 23.21 0.00 0.76 0.00 0.84 0.00
90 340.26 0.00 21.78 0.00 19.71 0.00 21.45 0.00 0.90 0.00 0.98 0.00
100 1534.94 0.00 17.99 0.00 14.47 0.00 15.89 0.00 0.80 0.00 0.88 0.00
200 745.81 0.00 14.05 0.00 8.12 0.00 9.02 0.00 0.58 0.00 0.64 0.00
Households by Density, Model Prediction vs. 2017 NHTS Data

Figure 30: Households by Density, Model Prediction vs. 2017 NHTS Data

Scatterplot of Model Prediction vs. 2017 NHTS Data by Density

Figure 31: Scatterplot of Model Prediction vs. 2017 NHTS Data by Density

Households by Household Size

HH Size Metro WgtHH Non-Metro WgtHH Metro Obs AADVMT/HH Non-Metro Obs AADVMT/HH Metro Pred AADVMT/HH Non-Metro Pred AADVMT/HH Metro Sim AADVMT/HH Non-Metro Sim AADVMT/HH Metro Ratio Pred/Obs Non-Metro Ratio Pred/Obs Metro Ratio Sim/Obs Non-Metro Ratio Sim/Obs
1 24789.06 11197.58 25.53 32.21 22.06 28.61 24.50 30.95 0.86 0.89 0.96 0.96
2 26608.61 16960.42 51.21 63.37 44.82 56.58 49.50 61.12 0.88 0.89 0.97 0.96
3 12654.71 7373.92 66.79 86.17 59.59 76.34 66.10 82.51 0.89 0.89 0.99 0.96
4 11564.15 6646.89 76.17 92.09 70.21 87.08 77.97 94.55 0.92 0.95 1.02 1.03
5 4237.91 2569.86 82.70 96.30 76.46 93.58 84.21 102.32 0.92 0.97 1.02 1.06
6 1990.78 1561.39 87.73 98.17 80.39 98.63 88.47 108.61 0.92 1.00 1.01 1.11
Households by Size, Model Prediction vs. 2017 NHTS Data

Figure 32: Households by Size, Model Prediction vs. 2017 NHTS Data

Scatterplot of Model Prediction vs. 2017 NHTS Data by Household Size

Figure 33: Scatterplot of Model Prediction vs. 2017 NHTS Data by Household Size

Households by Number of Workers

Workers Metro WgtHH Non-Metro WgtHH Metro Obs AADVMT/HH Non-Metro Obs AADVMT/HH Metro Pred AADVMT/HH Non-Metro Pred AADVMT/HH Metro Sim AADVMT/HH Non-Metro Sim AADVMT/HH Metro Ratio Pred/Obs Non-Metro Ratio Pred/Obs Metro Ratio Sim/Obs Non-Metro Ratio Sim/Obs
0 20272.01 14259.20 26.12 38.11 22.73 33.11 25.03 35.86 0.87 0.87 0.96 0.94
1 32098.30 15923.76 45.36 61.07 39.26 54.51 43.59 58.91 0.87 0.89 0.96 0.96
2 24216.64 13087.66 71.27 90.16 63.56 82.90 70.34 89.60 0.89 0.92 0.99 0.99
3 4117.97 2476.37 97.72 122.47 93.33 120.93 103.90 132.76 0.96 0.99 1.06 1.08
4 946.56 492.77 111.72 147.83 121.16 157.61 132.34 176.69 1.08 1.07 1.18 1.20
5 193.75 70.30 140.81 166.75 155.80 199.52 167.67 211.89 1.11 1.20 1.19 1.27
Households by Workers, Model Prediction vs. 2017 NHTS Data

Figure 34: Households by Workers, Model Prediction vs. 2017 NHTS Data

Scatterplot of Model Prediction vs. 2017 NHTS Data by Number of Workers

Figure 35: Scatterplot of Model Prediction vs. 2017 NHTS Data by Number of Workers

Households by Number of Drivers

Drivers Metro WgtHH Non-Metro WgtHH Metro Obs AADVMT/HH Non-Metro Obs AADVMT/HH Metro Pred AADVMT/HH Non-Metro Pred AADVMT/HH Metro Sim AADVMT/HH Non-Metro Sim AADVMT/HH Metro Ratio Pred/Obs Non-Metro Ratio Pred/Obs Metro Ratio Sim/Obs Non-Metro Ratio Sim/Obs
0 6379.97 1775.17 3.85 9.84 0.25 1.03 0.27 1.11 0.06 0.10 0.07 0.11
1 29495.36 13951.77 32.60 37.45 29.17 34.94 32.36 37.69 0.89 0.93 0.99 1.01
2 35930.38 23755.21 63.11 74.32 55.31 66.30 61.06 71.57 0.88 0.89 0.97 0.96
3 7247.26 5182.03 90.69 106.80 82.52 98.45 91.83 107.42 0.91 0.92 1.01 1.01
4 2304.52 1334.13 115.70 132.76 115.86 140.35 129.32 155.96 1.00 1.06 1.12 1.17
5 487.74 311.76 141.30 152.69 153.66 174.99 167.92 192.27 1.09 1.15 1.19 1.26
Households by Drivers, Model Prediction vs. 2017 NHTS Data

Figure 36: Households by Drivers, Model Prediction vs. 2017 NHTS Data

Scatterplot of Model Prediction vs. 2017 NHTS Data by Number of Drivers

Figure 37: Scatterplot of Model Prediction vs. 2017 NHTS Data by Number of Drivers

Households by Number of Vehicles

Vehicles Metro WgtHH Non-Metro WgtHH Metro Obs AADVMT/HH Non-Metro Obs AADVMT/HH Metro Pred AADVMT/HH Non-Metro Pred AADVMT/HH Metro Sim AADVMT/HH Non-Metro Sim AADVMT/HH Metro Ratio Pred/Obs Non-Metro Ratio Pred/Obs Metro Ratio Sim/Obs Non-Metro Ratio Sim/Obs
0 9450.20 2447.69 4.87 11.75 1.77 3.46 1.97 3.83 0.36 0.29 0.40 0.33
1 30794.10 13467.79 32.90 34.11 28.66 30.54 31.58 32.90 0.87 0.90 0.96 0.96
2 27652.77 17062.92 65.09 67.59 57.73 62.45 63.87 67.74 0.89 0.92 0.98 1.00
3 9612.37 8683.57 89.51 95.08 82.55 87.74 91.78 95.04 0.92 0.92 1.03 1.00
4 3178.56 3147.38 114.81 122.67 109.59 115.95 122.02 126.83 0.95 0.95 1.06 1.03
5 929.64 1024.81 135.14 150.15 129.55 134.16 143.88 144.22 0.96 0.89 1.06 0.96
6 145.64 321.20 153.36 151.92 139.53 145.57 151.79 155.16 0.91 0.96 0.99 1.02
7 42.84 89.25 202.63 164.16 131.76 121.27 142.66 129.09 0.65 0.74 0.70 0.79
8 7.87 34.92 179.52 194.60 157.32 139.88 191.98 150.94 0.88 0.72 1.07 0.78
9 16.31 23.77 119.83 216.79 161.06 139.90 186.17 189.98 1.34 0.65 1.55 0.88
10 14.81 1.16 152.66 136.10 112.34 97.20 118.17 94.30 0.74 0.71 0.77 0.69
11 0.00 4.59 0.00 209.79 0.00 110.76 0.00 156.09 0.00 0.53 0.00 0.74
12 0.10 1.03 123.96 221.19 75.21 113.23 79.06 114.69 0.61 0.51 0.64 0.52
Households by Drivers, Model Prediction vs. 2017 NHTS Data

Figure 38: Households by Drivers, Model Prediction vs. 2017 NHTS Data

Scatterplot of Model Prediction vs. 2017 NHTS Data by Number of Vehicles

Figure 39: Scatterplot of Model Prediction vs. 2017 NHTS Data by Number of Vehicles

Benchmarking Against 2009 Multimodal Model

The following tables and chart compare the performance of the 2009 and 2017 AADVMT Models by applying the 2009 model to the 2017 NHTS households.

Metro or Non-Metro Num HH NHTS2017 AADVMT/HH Model (2017) AADVMT/HH Model (2009) AADVMT/HH Ratio Model (2017)/NHTS2017 Ratio Model (2009)/NHTS2017
metro 71657 51.89 51.26 42.44 0.99 0.82
non_metro 56621 66.59 65.92 54.05 0.99 0.81
Scatterplot of 2009 Model Prediction vs. 2017 NHTS Data

Figure 40: Scatterplot of 2009 Model Prediction vs. 2017 NHTS Data

Scatterplot of 2009 Model Prediction vs. 2017 Model Prediction

Figure 41: Scatterplot of 2009 Model Prediction vs. 2017 Model Prediction